CN111950917A - Comprehensive evaluation method for drivability of multi-gear pure electric vehicle - Google Patents
Comprehensive evaluation method for drivability of multi-gear pure electric vehicle Download PDFInfo
- Publication number
- CN111950917A CN111950917A CN202010831860.5A CN202010831860A CN111950917A CN 111950917 A CN111950917 A CN 111950917A CN 202010831860 A CN202010831860 A CN 202010831860A CN 111950917 A CN111950917 A CN 111950917A
- Authority
- CN
- China
- Prior art keywords
- drivability
- index
- electric vehicle
- pure electric
- comprehensive evaluation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000011156 evaluation Methods 0.000 title claims abstract description 38
- 238000000034 method Methods 0.000 claims abstract description 19
- 230000008569 process Effects 0.000 claims abstract description 14
- 230000004044 response Effects 0.000 claims description 29
- 238000012360 testing method Methods 0.000 claims description 14
- 230000001133 acceleration Effects 0.000 claims description 9
- 230000002860 competitive effect Effects 0.000 claims description 9
- 239000011159 matrix material Substances 0.000 claims description 9
- 230000001052 transient effect Effects 0.000 claims description 7
- 238000005457 optimization Methods 0.000 claims description 4
- 230000009286 beneficial effect Effects 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 230000018109 developmental process Effects 0.000 description 2
- 238000007689 inspection Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000000750 progressive effect Effects 0.000 description 2
- 238000012163 sequencing technique Methods 0.000 description 2
- 239000002131 composite material Substances 0.000 description 1
- 230000002950 deficient Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000005611 electricity Effects 0.000 description 1
- 230000005484 gravity Effects 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 108090000623 proteins and genes Proteins 0.000 description 1
- 238000011002 quantification Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000011218 segmentation Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/067—Enterprise or organisation modelling
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Operations Research (AREA)
- Marketing (AREA)
- Game Theory and Decision Science (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Testing Of Devices, Machine Parts, Or Other Structures Thereof (AREA)
Abstract
The invention relates to a comprehensive evaluation method for drivability of a multi-gear pure electric vehicle, which specifically comprises the following steps: s1, establishing a drivability index system of the pure electric vehicle; s2, acquiring the weight value of each drivability index based on an analytic hierarchy process; and S3, calculating a comprehensive driving score based on the weighted values and the subjective scores of the driving indexes. And calculating a relatively objective comprehensive evaluation result of the drivability based on the combination of the weight values of the various drivability indexes objectively quantified and the subjective evaluation.
Description
Technical Field
The invention relates to the technical field of driving performance evaluation, and provides a comprehensive evaluation method for the driving performance of a multi-gear pure electric vehicle.
Background
The automobile drivability evaluation belongs to an indispensable module in a whole automobile evaluation system, and is in a higher and higher position in a whole automobile performance development system. The development target of the drivability is mainly to improve the driving expectation of the driver and realize the optimal driving experience. The driving performance of a vehicle type reflects the unique market positioning and the brand genes of the vehicle product.
Regarding the method for evaluating the driving performance and the segmentation dimension, different vehicle enterprises have different understanding and division according to the own vehicle types; most often still based on the subjective assessment of the engineer, the composite score is replaced by a mean. Due to the lack of weight quantification, the method is difficult to obtain a more accurate result; for indexes with the same score, specific optimization and modification directions lack clear guidance. In addition, most of current pure electric vehicles adopt a single-stage main reduction structure (only one forward gear), and pure electric vehicles with two or more automatic gearboxes are synchronously developed, so that the division and comprehensive evaluation of the drivability index of the vehicle are relatively more complex.
Disclosure of Invention
The invention provides a comprehensive evaluation method for drivability of a multi-gear pure electric vehicle, which is used for calculating a relatively objective comprehensive evaluation result of drivability based on combination of subjective evaluation and weight values for objectively quantifying each drivability index.
The invention discloses a comprehensive evaluation method for drivability of a multi-gear pure electric vehicle, which specifically comprises the following steps:
s1, establishing a drivability index system of the pure electric vehicle;
s2, acquiring the weight value of each drivability index based on an analytic hierarchy process;
and S3, calculating a comprehensive driving score based on the weighted values and the subjective scores of the driving indexes.
Further, the step S2 specifically includes the following steps:
s21, constructing a hierarchical structure model based on the driving index system;
s22, establishing a matrix table of each layer based on the scale value of each drivability index;
and S23, calculating the weight value of each driving performance index based on the matrix table of each layer.
Further, the drivability index system includes: the system comprises three performance indexes of start/stop B1, acceleration/deceleration response B2 and gear shifting B3, wherein each performance index is divided into the following parts:
the start/stop B1 performance index includes three sub-performance indexes: a power-on starting transient response C1, a power-off flameout transient response C2 and a simulated idle stability C3;
the acceleration/deceleration response B2 performance index includes five sub-performance indexes: full load response C4, part load response C5, steady state response C6, tip in/out response C7, and accelerator pedal force/stroke C8;
the shift B3 performance index includes four sub-performance indexes: smooth upshift C9, smooth downshift C10, shift logic C11, and shift quality C12.
Further, a comprehensive score S of drivabilitycalThe calculation formula is as follows:
in the formula, SCiIs the subjective evaluation score of the Ci-th drivability index, WCiIs the weight value of the Ci-th drivability index.
Further, the following steps are included after step S3:
and S4, determining the optimized direction of the test vehicle based on the weighted value of the drivability index.
Further, the step S4 specifically includes the following steps:
s41, acquiring a drivability index with a high weight value in the test vehicle;
s42, acquiring subjective scores of the test vehicle and the competitive vehicle under the drivability index;
and S43, performing relevant optimization on the test vehicle by taking the competitive vehicle with high subjective score as a reference object.
Furthermore, the electric vehicle is provided with a plurality of forward gears.
The comprehensive evaluation method for the drivability of the multi-gear pure electric vehicle has the following beneficial effects:
1) the self-adaptive gear shifting system is suitable for a pure electric vehicle drivability index system carrying multiple forward gears and self-adaptive gear shifting;
2) objectively quantifying the weight value of each drivability index by combining an improved analytic hierarchy process, combining the subjective evaluation with the objective evaluation, and finally calculating a relatively objective drivability comprehensive evaluation result;
3) the correcting direction is determined by referring to two dimensions of weight sequencing and subjective score of the driving indexes and combining the competitive product data, so that the calibration time can be saved, and the correcting efficiency can be improved.
Drawings
FIG. 1 is a flowchart of a comprehensive evaluation method for drivability of a multi-gear pure electric vehicle according to an embodiment of the present invention;
fig. 2 is a schematic diagram of a hierarchical model of a drivability index system according to an embodiment of the present invention.
Detailed Description
The following description of preferred embodiments of the invention will be made in further detail with reference to the accompanying drawings.
Fig. 1 is a flowchart of a comprehensive evaluation method for drivability of a multi-gear pure electric vehicle according to an embodiment of the present invention, and the comprehensive evaluation method for drivability is described with reference to fig. 1, specifically as follows:
the driving performance indexes suitable for the multi-gear pure electric automobile are divided into three types of performance indexes, namely start/stop B1, acceleration/deceleration response B2 and gear shifting B3. Each performance index is subdivided again: the start/stop B1 packet performance indicators include: three sub-performance indexes of a power-on starting transient response C1, a power-off flameout transient response C2 and a simulated idle stability C3; the acceleration/deceleration response B2 includes: five performance sub-indexes of full load response C4 (full opening of an accelerator pedal), partial load response C5 (full opening of the accelerator pedal), steady state response C6 (stable stroke of the accelerator pedal), tip in/out response (tip in treading the accelerator pedal and tip out releasing the accelerator pedal) C7 and accelerator pedal force/stroke C8; shift B3 includes: the four performance sub-indexes of the gear-shifting smoothness C9, the gear-shifting smoothness C10, the gear-shifting logic C11 and the gear-shifting operation quality C12.
Wherein, the start/stop B1 reflects the transient response performance of vehicle power-on and power-off and the performance of simulated idling (READY gear standing) state; the acceleration/deceleration response B2 mainly reflects the load response during the dynamic driving process; the shift B3 mainly represents the smoothness of shift switching during driving, the control logic of automatic shifting, and the operation quality of the shifter, and a hierarchical model is established according to a drivability index system as shown in fig. 2.
Use of improved analytic hierarchy process
In the actual use process of the traditional analytic hierarchy process, the subjective judgment and the selection preference of a decision maker are important; if the experience is insufficient and the judgment is wrong, the decision deviation can be caused. The evaluator needs to understand the essential connotation of the decision problem, the composition of each element and the interrelationship thereof, and the like sufficiently and thoroughly. The invention analyzes by referring to a method for modifying a scale value, and the progressive gradient in the traditional analytic hierarchy process is 3 → 1.7 → 1.4 → 1.3 (for example, the progressive gradient from 'equal' to 'slight' is 3, but the gradient from 'slight' to 'obvious' is only 1.7, and the difference is larger); improved analytic hierarchy process corresponds to a gradient of 1.3 → 1.4 → 1.7 → 3 (relatively more acceptable); see table 1 below.
TABLE 1 improved analytic hierarchy Process decision matrix Scale comparison
A, establishing a driving hierarchical model
A professional subjective evaluation engineer evaluates and scores the test sample vehicle, and the result is shown in a table 2; the table simultaneously gives the evaluation results of two competitive products vehicles BM1 and BM 2; it can be seen that the total score S is based on the driveabilityavgEasily obtain the test vehicle and two racing vehiclesTotal drivability score S of BM1 and BM2avgThe same values, the drivability level was comparable.
TABLE 2 subjective scoring sheet
B structure judgment matrix
For pure electric vehicles, the difference between the up/down electricity performance is relatively small, and the large difference between the acceleration/deceleration response and the gear shifting performance is easy to occur. In acceleration/deceleration response, the emphasis and difficulty are often found in C5 and C7; and C9 and C10 tend to occupy larger specific gravity in the shifting performance. In conjunction with the improved scale values described above, a decision matrix (consistency check will be performed later) at each corresponding level is constructed accordingly. The statistical results are detailed in tables 3 and 4.
TABLE 3A-B decision matrix Table
| A | B1 | B2 | B3 |
| B1 | 9/9 | 5/9 | 5/9 |
| B2 | 9/5 | 9/9 | 9/7 |
| B3 | 9/5 | 7/9 | 9/9 |
TABLE 4B-C decision matrix Table
| B1 | C1 | C2 | C3 | - | - |
| C1 | 9/9 | 5/9 | 5/9 | - | - |
| C2 | 9/5 | 9/9 | 9/7 | - | - |
| C3 | 9/5 | 7/9 | 9/9 | - | - |
| B2 | C4 | C5 | C6 | C7 | C8 |
| C4 | 9/9 | 7/9 | 7/9 | 5/9 | 7/9 |
| C5 | 9/7 | 9/9 | 7/9 | 7/9 | 9/9 |
| C6 | 9/7 | 9/7 | 9/9 | 9/9 | 9/7 |
| C7 | 9/5 | 9/7 | 9/9 | 9/9 | 9/5 |
| C8 | 9/7 | 9/9 | 7/9 | 5/9 | 9/9 |
| B3 | C9 | C10 | C11 | C12 | - |
| C9 | 9/9 | 9/9 | 9/4 | 9/4 | - |
| C10 | 9/9 | 9/9 | 9/5 | 9/4 | - |
| C11 | 4/9 | 5/9 | 9/9 | 9/7 | - |
| C12 | 4/9 | 4/9 | 7/9 | 9/9 | - |
C-level single ordering and inspection
According to the analytic hierarchy process solving mechanism, by MATLAB programming, corresponding M file calculation is run, so that the hierarchical single ordering weight (calculated by the sum-method programming) and the Consistency Ratio (CR) test result can be obtained, and the summary is shown in Table 5. It can be found that all CR values are less than 0.1; thus, all single-level uniformity may be considered satisfactory.
TABLE 5 Single rank weights and tests
D-level Total ordering and inspection
After each level of individual consistency check, the overall ordering and check is still required. According to the M file operation, the total consistency ratio is 0.0094 (less than 0.1); so far, it is reasonable that we can be derived that the overall consistency of the constructed hierarchical model is reasonable.
TABLE 6 Total sorting weights and tests
Comparison of evaluation results
Comparing the calculated scores based on a driving comprehensive score calculation formula, wherein the results have certain difference; therefore, if the subjective evaluation result is simply relied on, the accuracy is deficient by adopting the mean value calculation; meanwhile, the selection of the later rectification direction is not facilitated. And the later rectification and optimization direction can be determined by comparing the data with the competitive product data. In practical engineering application, generally, a driving index with a high weight value is selected preferentially, and a more ideal score in the competitive product data is used as a reference; the two dimensions of reference weight sorting and subjective score are adopted, so that the calibration time can be saved, and the rectification efficiency can be improved.
Comprehensive score S of drivabilitycalThe calculation formula is as follows:
in the formula, SCiIs the subjective evaluation score of the Ci-th drivability index, WCiIs the weight value of the Ci-th drivability index.
TABLE 8 weight calculation score comparison
Comprehensive score S of drivability of test vehicles in table 8calThe calculation formula is as follows:
Scal＝0.0780*7.5+0.0607*7.5+0.0780*8.0+0.0636*5.5+0.0789*6.0+0.0968*5.5+0.1109*6.0+0.0740*8.0+0.1254*7.0+0.1184*7.0+0.0628*8.0+0.0523*8.0
the comprehensive evaluation method for the drivability of the multi-gear pure electric vehicle has the following beneficial effects:
1) the self-adaptive gear shifting system is suitable for a pure electric vehicle drivability index system carrying multiple forward gears and self-adaptive gear shifting;
2) objectively quantifying the weight value of each drivability index by combining an improved analytic hierarchy process, combining the subjective evaluation with the objective evaluation, and finally calculating a relatively objective drivability comprehensive evaluation result;
3) the correcting direction is determined by referring to two dimensions of weight sequencing and subjective score of the driving indexes and combining the competitive product data, so that the calibration time can be saved, and the correcting efficiency can be improved.
It is clear that the specific implementation of the invention is not restricted to the above-described embodiments, but that various insubstantial modifications of the inventive process concept and technical solutions are within the scope of protection of the invention.
Claims (7)
1. The comprehensive evaluation method for the drivability of the multi-gear pure electric vehicle is characterized by comprising the following steps of:
s1, establishing a drivability index system of the pure electric vehicle;
s2, acquiring the weight value of each drivability index based on an analytic hierarchy process;
and S3, calculating a comprehensive driving score based on the weighted values and the subjective scores of the driving indexes.
2. The comprehensive evaluation method for drivability of the multi-gear pure electric vehicle according to claim 1, wherein the step S2 specifically includes the following steps:
s21, constructing a hierarchical structure model based on the driving index system;
s22, establishing a matrix table of each layer based on the scale value of each drivability index;
and S23, calculating the weight value of each driving performance index based on the matrix table of each layer.
3. The comprehensive evaluation method for the drivability of the multi-gear pure electric vehicle according to claim 1, wherein the drivability index system comprises: the system comprises three performance indexes of start/stop B1, acceleration/deceleration response B2 and gear shifting B3, wherein each performance index is divided into the following parts:
the start/stop B1 performance index includes three sub-performance indexes: a power-on starting transient response C1, a power-off flameout transient response C2 and a simulated idle stability C3;
the acceleration/deceleration response B2 performance index includes five sub-performance indexes: full load response C4, part load response C5, steady state response C6, tip in/out response C7, and accelerator pedal force/stroke C8;
the shift B3 performance index includes four sub-performance indexes: smooth upshift C9, smooth downshift C10, shift logic C11, and shift quality C12.
4. The method for comprehensively evaluating the drivability of the multi-gear pure electric vehicle according to claim 1, wherein a comprehensive score S of drivability is obtainedcalThe calculation formula is as follows:
in the formula, SCiIs the subjective evaluation score of the Ci-th drivability index, WCiIs the weight value of the Ci-th drivability index.
5. The comprehensive evaluation method for drivability of the multi-gear pure electric vehicle according to claim 1, further comprising the following steps after step S3:
and S4, determining the optimized direction of the test vehicle based on the weighted value of the drivability index.
6. The comprehensive evaluation method for drivability of the multi-gear pure electric vehicle according to claim 5, wherein the step S4 specifically includes the following steps:
s41, acquiring a drivability index with a high weight value in the test vehicle;
s42, acquiring subjective scores of the test vehicle and the competitive vehicle under the drivability index;
and S43, performing relevant optimization on the test vehicle by taking the competitive vehicle with high subjective score as a reference object.
7. The comprehensive evaluation method for the drivability of the multi-gear pure electric vehicle according to claim 1, wherein the electric vehicle is provided with a plurality of forward gears.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010831860.5A CN111950917A (en) | 2020-08-18 | 2020-08-18 | Comprehensive evaluation method for drivability of multi-gear pure electric vehicle |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010831860.5A CN111950917A (en) | 2020-08-18 | 2020-08-18 | Comprehensive evaluation method for drivability of multi-gear pure electric vehicle |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111950917A true CN111950917A (en) | 2020-11-17 |
Family
ID=73343031
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010831860.5A Pending CN111950917A (en) | 2020-08-18 | 2020-08-18 | Comprehensive evaluation method for drivability of multi-gear pure electric vehicle |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111950917A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112598229A (en) * | 2020-12-07 | 2021-04-02 | 安徽江淮汽车集团股份有限公司 | Vehicle stability scoring test method, system and storage medium |
| CN113029593A (en) * | 2021-03-26 | 2021-06-25 | 奇瑞新能源汽车股份有限公司 | Method and device for evaluating drivability of automobile |
| CN114066015A (en) * | 2021-10-22 | 2022-02-18 | 山东旗帜信息有限公司 | Department personnel composition optimization method, equipment and medium |
| CN114118517A (en) * | 2021-10-13 | 2022-03-01 | 北京汽车集团越野车有限公司 | Parameter optimization method and device |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106202872A (en) * | 2016-06-27 | 2016-12-07 | 江苏迪纳数字科技股份有限公司 | Vehicle driving behavior scoring method |
| CN108510172A (en) * | 2018-03-23 | 2018-09-07 | 同济大学 | A kind of assessment indicator system for vehicle driving |
| US20190251586A1 (en) * | 2018-02-09 | 2019-08-15 | Cox Automotive, Inc. | Systems and methods of predictive modeling for evaluating vehicles |
| CN110826848A (en) * | 2019-09-19 | 2020-02-21 | 安徽百诚慧通科技有限公司 | Driver risk assessment method based on analytic hierarchy process |
| CN111047142A (en) * | 2019-11-14 | 2020-04-21 | 佛山科学技术学院 | Automobile scoring method and system based on analytic hierarchy process |
| CN111428960A (en) * | 2020-01-10 | 2020-07-17 | 武汉理工大学 | Intelligent vehicle driving automatic evaluation method fusing multi-source vehicle-mounted sensor information |
| CN111461475A (en) * | 2019-01-18 | 2020-07-28 | 华北电力大学（保定） | Method for evaluating performance state of electric vehicle charging equipment |
-
2020
- 2020-08-18 CN CN202010831860.5A patent/CN111950917A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106202872A (en) * | 2016-06-27 | 2016-12-07 | 江苏迪纳数字科技股份有限公司 | Vehicle driving behavior scoring method |
| US20190251586A1 (en) * | 2018-02-09 | 2019-08-15 | Cox Automotive, Inc. | Systems and methods of predictive modeling for evaluating vehicles |
| CN108510172A (en) * | 2018-03-23 | 2018-09-07 | 同济大学 | A kind of assessment indicator system for vehicle driving |
| CN111461475A (en) * | 2019-01-18 | 2020-07-28 | 华北电力大学（保定） | Method for evaluating performance state of electric vehicle charging equipment |
| CN110826848A (en) * | 2019-09-19 | 2020-02-21 | 安徽百诚慧通科技有限公司 | Driver risk assessment method based on analytic hierarchy process |
| CN111047142A (en) * | 2019-11-14 | 2020-04-21 | 佛山科学技术学院 | Automobile scoring method and system based on analytic hierarchy process |
| CN111428960A (en) * | 2020-01-10 | 2020-07-17 | 武汉理工大学 | Intelligent vehicle driving automatic evaluation method fusing multi-source vehicle-mounted sensor information |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112598229A (en) * | 2020-12-07 | 2021-04-02 | 安徽江淮汽车集团股份有限公司 | Vehicle stability scoring test method, system and storage medium |
| CN113029593A (en) * | 2021-03-26 | 2021-06-25 | 奇瑞新能源汽车股份有限公司 | Method and device for evaluating drivability of automobile |
| CN114118517A (en) * | 2021-10-13 | 2022-03-01 | 北京汽车集团越野车有限公司 | Parameter optimization method and device |
| CN114066015A (en) * | 2021-10-22 | 2022-02-18 | 山东旗帜信息有限公司 | Department personnel composition optimization method, equipment and medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111950917A (en) | Comprehensive evaluation method for drivability of multi-gear pure electric vehicle | |
| CN107218385B (en) | Slide the power downshift control method in downshift | |
| US20170037959A1 (en) | Method for evaluating the shifting behavior of a motor vehicle transmission | |
| CN102749206B (en) | Vehicle gear-shifting quality evaluation testing method and system | |
| US20170206307A1 (en) | Systems and methods for determining speed control management settings | |
| CN112943914B (en) | Vehicle gear shifting line determining method and device, computer equipment and storage medium | |
| CN113029593A (en) | Method and device for evaluating drivability of automobile | |
| CN1598523A (en) | System testing method of multiple working condition loading of vehicle table amalog road test | |
| CN113565954B (en) | Gear shifting optimization method and system based on working conditions | |
| CN113987685B (en) | Whole vehicle performance simulation method and device under multiple working conditions of pure electric vehicle | |
| Newman et al. | Development and testing of an automatic transmission shift schedule algorithm for vehicle simulation | |
| CN112508317A (en) | Subjective and objective relevance scoring method based on multi-source power assembly vehicle type drivability | |
| Chandrasekaran et al. | Objective drivability evaluation on compact SUV and comparison with subjective drivability | |
| CN101368624B (en) | Selection and service life assessment method for automobile speed variator bearing | |
| GB2535700A (en) | A method for reducing the amount of fuel used by an engine of a motor vehicle | |
| Singh et al. | Selection of gear ratio for smooth gear shifting | |
| CN107989704B (en) | Engine gear shifting prompt parameter acquisition system and method | |
| CN108216253B (en) | Driver type recognition control function module framework and control system of vehicle | |
| Lei et al. | Research on optimal gearshift strategy for stepped automatic transmission based on vehicle power demand | |
| Chen et al. | GSA test analysis and optimization strategy for shifting quality of automobile transmission | |
| CN113887909A (en) | Method for evaluating total life cycle cost of airplane | |
| CN110322111B (en) | Performance evaluation method of mechanical product based on Bayesian network | |
| CN115438479A (en) | Dual-motor hybrid power assembly model selection evaluation system and method and medium | |
| Jeong et al. | Automated Model Initialization Using Test Data | |
| KR20230094877A (en) | Artificial intelligence based apparatus and method for calibration of transmission control unit |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20201117 |
|
| RJ01 | Rejection of invention patent application after publication |